371 research outputs found
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Architectures for Real-Time Volume Rendering
Over the last decade, volume rendering has become an invaluable visualization technique for a wide variety of applications. This paper reviews three special-purpose architectures for interactive volume rendering: texture mapping, VIRIM, and VolumePro. Commercial implementations of these architectures are available or underway. The discussion of each architecture will focus on the algorithm, system architecture, memory system, and volume rendering performance.Engineering and Applied Science
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3D TV: A Scalable System for Real-Time Acquisition, Transmission, and Autostereoscopic Display of Dynamic Scenes
Three-dimensional TV is expected to be the next revolution in the history of television. We implemented a 3D TV prototype system with real-time acquisition, transmission, and 3D display of dynamic scenes. We developed a distributed, scalable architecture to manage the high computation and bandwidth demands. Our system consists of an array of cameras, clusters of network-connected PCs, and a multi-projector 3D display. Multiple video streams are individually encoded and sent over a broadband network to the display. The 3D display shows high-resolution (1024 × 768) stereoscopic color images for multiple viewpoints without special glasses. We implemented systems with rear-projection and front-projection lenticular screens. In this paper, we provide a detailed overview of our 3D TV system, including an examination of design choices and tradeoffs. We present the calibration and image alignment procedures that are necessary to achieve good image quality. We present qualitative results and some early user feedback. We believe this is the first real-time end-to-end 3D TV system with enough views and resolution to provide a truly immersive 3D experience.Engineering and Applied Science
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Cube-4 - A Scalable Architecture for Real-Time Volume Rendering
We present Cube-4, a special-purpose volume rendering architecture
that is capable of rendering high-resolution (e.g., 1024^3)
datasets at 30 frames per second. The underlying algorithm, called
slice-parallel ray-casting, uses tri-linear interpolation of samples
between data slices for parallel and perspective projections. The
architecture uses a distributed interleavedmemory, several parallel
processing pipelines, and an innovative parallel dataflow scheme
that requires no global communication, except at the pixel level.
This leads to local, fixed bandwidth interconnections and has the
benefits of high memory bandwidth, real-time data input, modularity,
and scalability. We have simulated the architecture and have
implemented a working prototype of the complete hardware on a
configurable custom hardware machine. Our results indicate true
real-time performance for high-resolution datasets and linear scalability
of performance with the number of processing pipelines.Engineering and Applied Science
Personalizing gesture recognition using hierarchical bayesian neural networks
Building robust classifiers trained on data susceptible to group or subject-specific variations is a challenging pattern recognition problem. We develop hierarchical Bayesian neural networks to capture subject-specific variations and share statistical strength across subjects. Leveraging recent work on learning Bayesian neural networks, we build fast, scalable algorithms for inferring the posterior distribution over all network weights in the hierarchy. We also develop methods for adapting our model to new subjects when a small number of subject-specific personalization data is available. Finally, we investigate active learning algorithms for interactively labeling personalization data in resource-constrained scenarios. Focusing on the problem of gesture recognition where inter-subject variations are commonplace, we demonstrate the effectiveness of our proposed techniques. We test our framework on three widely used gesture recognition datasets, achieving personalization performance competitive with the state-of-the-art.http://openaccess.thecvf.com/content_cvpr_2017/html/Joshi_Personalizing_Gesture_Recognition_CVPR_2017_paper.htmlhttp://openaccess.thecvf.com/content_cvpr_2017/html/Joshi_Personalizing_Gesture_Recognition_CVPR_2017_paper.htmlhttp://openaccess.thecvf.com/content_cvpr_2017/html/Joshi_Personalizing_Gesture_Recognition_CVPR_2017_paper.htmlPublished versio
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Object Space EWA Surface Splatting: A Hardware Accelerated Approach to High Quality Point Rendering
Elliptical weighted average (EWA) surface splatting is a technique for high quality rendering of point-sampled 3D objects. EWA surface splatting renders water-tight surfaces of complex point models with high quality, anisotropic texture filtering. In this paper we introduce a new multi-pass approach to perform EWA surface splatting on modern PC graphics hardware, called object space EWA splatting. We derive an object space formulation of the EWA filter, which is amenable for acceleration by conventional triangle-based graphics hardware. We describe how to implement the object space EWA filter using a two pass rendering algorithm. In the first rendering pass, visibility splatting is performed by shifting opaque surfel polygons backward along the viewing rays, while in the second rendering pass view-dependent EWA prefiltering is performed by deforming texture mapped surfel polygons. We use texture mapping and alpha blending to facilitate the splatting process. We implement our algorithm using programmable vertex and pixel shaders, fully exploiting the capabilities of today’s graphics processing units (GPUs). Our implementation renders up to 3 million points per second on recent PC graphics hardware, an order of magnitude more than a pure software implementation of screen space EWA surface splatting.Engineering and Applied Science
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Sheared Interpolation and Gradient Estimation for Real-Time Volume Renderings
In this paper we present a technique for the interactive
control and display of static and dynamic 3D datasets.
We describe novel ways of tri-linear interpolation and
gradient estimation for a real-time volume rendering
system, using coherency between rays. We show simulation results that compare the proposed methods to traditional algorithms and present them in the context of
Cube-3, a special-purpose architecture capable of rendering 5123 16-bit per voxel datasets at over 20 frames per
second.Engineering and Applied Science
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Towards a Scalable Architecture for Real-Time Volume Rendering
In this paper we present our research eff orts towards a
scalable volume rendering architecture for the real-time
visualization of dynamically changing high-resolution
datasets. Using a linearly skewed memory interleaving we were able to develop a parallel data
ow model
that leads to local, fixed-bandwidth interconnections between processing elements. This parallel dataflow model
diff ers from previous work in that it requires no global
communication of data except at the pixel level. Using this data
ow model we are developing Cube-4, an
architecture that is scalable to very high performances
and allows for modular and extensible hardware implementations.Engineering and Applied Science
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